• Tiffany Luu, Brian P Curran, Alvaro A Macias, Soraya Mehdipour, Sierra Simpson, and Rodney A Gabriel.
• From the Division of Perioperative Informatics, Department of Anesthesiology, University of California San Diego, La Jolla, California.
• Anesth. Analg. 2023 Nov 1; 137 (5): 103910461039-1046.

BackgroundPreoperative risk stratification for hepatectomy patients can aid clinical decision making. The objective of this retrospective cohort study was to determine postoperative mortality risk factors and develop a score-based risk calculator using a limited number of preoperative predictors to estimate mortality risk in patients undergoing hepatectomy.MethodsData were collected from patients that underwent hepatectomy from the National Surgical Quality Improvement Program dataset from 2014 to 2020. Baseline characteristics were compared between survival and 30-day mortality cohorts using the χ 2 test. Next, the data were split into a training set to build the model and a test set to validate the model. A multivariable logistic regression model modeling 30-day postoperative mortality was trained on the training set using all available features. Next, a risk calculator using preoperative features was developed for 30-day mortality. The results of this model were converted into a score-based risk calculator. A point-based risk calculator was developed that predicted 30-day postoperative mortality in patients who underwent hepatectomy surgery.ResultsThe final dataset included 38,561 patients who underwent hepatectomy. The data were then split into a training set from 2014 to 2018 (n = 26,397) and test set from 2019 to 2020 (n = 12,164). Nine independent variables associated with postoperative mortality were identified and included age, diabetes, sex, sodium, albumin, bilirubin, serum glutamic-oxaloacetic transaminase (SGOT), international normalized ratio, and American Society of Anesthesiologists classification score. Each of these features were then assigned points for a risk calculator based on their odds ratio. A univariate logistic regression model using total points as independent variables were trained on the training set and then validated on the test set. The area under the receiver operating characteristics curve on the test set was 0.719 (95% confidence interval, 0.681-0.757).ConclusionsDevelopment of risk calculators may potentially allow surgical and anesthesia providers to provide a more transparent plan to support patients planned for hepatectomy.Copyright © 2023 International Anesthesia Research Society.

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